Intraventricular blood flow with a fully dynamic mitral valve model

Mitral valve (MV) leaflets affect the formation, growth, and decay of vortices in the left ventricle (LV) during diastolic filling. The shape and motion of MV leaflets are simplified in most studies due to computational restrictions. In this study, we present a newly developed mathematical method to model the dynamic movement of valve leaflets and annulus, which is based on in vivo data obtained with magnetic resonance imaging (MRI). In the present method, we solve a boundary value problem where the MV surface is initially unknown. The resultant MV shapes are included in a dynamic motion model of the LV to assess the change of intraventricular flow patterns. To estimate the effects of the MV on left intraventricular flow, a LV model without MV leaflets was also simulated for comparison. Our study showed that the presence of the MV and the shape of its leaflets significantly altered the formation and evolution of vortex structures in the LV. The various MV leaflet shapes accelerate the transvalvular flow distinctly, leading to different formation and development of vortex structures.Cardiovascular Aspects of Radiolog

Modeling Left Ventricular Blood Flow Using Smoothed Particle Hydrodynamics

This study aims to investigate the capability of smoothed particle hydrodynamics (SPH), a fully Lagrangian mesh-free method, to simulate the bulk blood flow dynamics in two realistic left ventricular (LV) models. Three dimensional geometries and motion of the LV, proximal left atrium and aortic root are extracted from cardiac magnetic resonance imaging and multi-slice computed tomography imaging data. SPH simulation results are analyzed and compared with those obtained using a traditional finite volume-based numerical method, and to in vivo phase contrast magnetic resonance imaging and echocardiography data, in terms of the large-scale blood flow phenomena usually clinically measured. A quantitative comparison of the velocity fields and global flow parameters between the in silico models and the in vivo data shows a reasonable agreement, given the inherent uncertainties and limitations in the modeling and imaging techniques. The results indicate the capability of SPH as a promising tool for predicting clinically relevant large-scale LV flow information